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  1. Preface
  2. Introduction to Informatica Data Engineering Integration
  3. Mappings
  4. Mapping Optimization
  5. Sources
  6. Targets
  7. Transformations
  8. Python Transformation
  9. Data Preview
  10. Cluster Workflows
  11. Profiles
  12. Monitoring
  13. Hierarchical Data Processing
  14. Hierarchical Data Processing Configuration
  15. Hierarchical Data Processing with Schema Changes
  16. Intelligent Structure Models
  17. Blockchain
  18. Stateful Computing
  19. Appendix A: Connections Reference
  20. Appendix B: Data Type Reference
  21. Appendix C: Function Reference

Hive Complex Data Types

Hive Complex Data Types

Hive complex data types such as arrays, maps, and structs are a composite of primitive or complex data types. Informatica Developer represents complex data types with the string data type and uses delimiters to separate the elements of the complex data type.
You can read and write hierarchical data from Hive tables in a mapping that runs on the Spark engine.
The following table lists the complex data types:
Complex Data Type
Description
Array
An array contains an ordered collection of elements of same data type. The elements in an array are delimited by commas. For example, an array of
fruits
is represented as
[apple,banana,orange]
.
Map
A map contains an unordered collection of key-value pairs and are represented as pairs of strings and integers delimited by the
=
character. String and integer pairs are delimited by commas. For example, a map of
fruits
is represented as
[1=apple,2=banana,3=orange]
.
Struct
A struct contains a collection of elements of different data types delimited by the
:
character. String and integer pairs are delimited by commas. For example, a struct is represented as
struct {1:"apple" [, "apple":"red", ...]}
.


Updated September 28, 2020